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Found 3 papers, 3 papers with code
Simple linear attention language models balance the recall-throughput tradeoff
In this work, we explore whether we can improve language model efficiency (e. g. by reducing memory consumption) without compromising on recall.
Zoology: Measuring and Improving Recall in Efficient Language Models
To close the gap between synthetics and real language, we develop a new formalization of the task called multi-query associative recall (MQAR) that better reflects actual language.
How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections
Linear time-invariant state space models (SSM) are a classical model from engineering and statistics, that have recently been shown to be very promising in machine learning through the Structured State Space sequence model (S4).
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